We compute the leptonic decay constants f D + , f Ds , and f K + , and the quark-mass ratios m c /m s and m s /m l in unquenched lattice QCD using the experimentally determined value of f π + for normalization. We use the MILC Highly Improved Staggered Quark ( |V cs | = 1.010(5)(18)(6), where the errors are from this calculation of the decay constants, the uncertainty in the experimental decay rates, structure-dependent electromagnetic corrections, and, in the case of |V us |, the uncertainty in |V ud |, respectively.

We present preliminary results for light, strange and charmed pseudoscalar meson physics from simulations using four flavors of dynamical quarks with the highly improved staggered quark (HISQ) action. These simulations include lattice spacings ranging from 0.15 to 0.06 fm, and seaquark masses both above and at their physical value. The major results are charm meson decay constants f D , f D s and f D s / f D and ratios of quark masses. This talk will focus on our procedures for finding the decay constants on each ensemble, the continuum extrapolation, and estimates of systematic error.

This article describes an implementation of real-time simulation and control in DEVS-Scheme, a knowledge-based, discrete event environment. We illustrate a methodology in which the plant, its actuators and sensors are described by discrete event models developed within the event-based control paradigm. A model of the controller is employed to validate its design in a plant/actuator/sensor experimental frame. The same model con guration is then employed for actual control operation by connecting the simulation executive, suitably modi ed, to a programmable controller that interfaces to the real plant/actuator/sensor system. We show how this methodology is supported by real-time interpretation of the DEVS (Discrete Event System Speci cation) formalism. A lower bound on the processing speed of a non-deterministic operating system relative to scheduled event times is derived which guarantees correct control timing. We show how the DEVS-based control can be distributed in a hierarchical manner to ensure that the required deadline time constraints are met. As an example, an intelligent controller is discussed for a prototype oxygen extraction system eventually intended to operate autonomously on Mars. We conclude that DEVS provides a exible discrete event formalism for knowledge-based real-time control applications.

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